Personal Knowledge Assistant MCP Server

A comprehensive Model Context Protocol (MCP) server that transforms how you manage and analyze your personal information across email, social media, documents, and productivity metrics.

🚀 Features

📧 Email Intelligence

• Smart Email Management: Search, analyze, and compose emails with AI assistance
• Communication Pattern Analysis: Understand your email habits, response times, and relationship dynamics
• Thread Analysis: Track email conversations and extract actionable insights
• Automated Categorization: Intelligent labeling and organization of your inbox

🌐 Social Media Integration

• Multi-Platform Support: Twitter, LinkedIn, Facebook, and Instagram
• Content Performance Analysis: Track engagement metrics, reach, and audience insights
• Optimal Timing: AI-powered recommendations for when to post
• Cross-Platform Publishing: Post to multiple platforms simultaneously

📁 Document Management

• Universal Search: Find documents across Google Drive, Dropbox, and local files
• Content Analysis: Extract key insights and summaries from documents
• Version Tracking: Monitor document changes and collaboration patterns
• Smart Organization: Automatic tagging and categorization

📊 Personal Analytics

• Productivity Metrics: Track work patterns, focus time, and task completion
• Habit Monitoring: Build and maintain positive habits with data-driven insights
• Goal Progress: Monitor and analyze progress toward personal and professional goals
• Health & Wellness: Integrate mood, energy, and wellness tracking

🧠 AI-Powered Insights

• Behavioral Pattern Detection: Identify trends in your communication and work habits
• Predictive Analytics: Anticipate busy periods and optimize your schedule
• Relationship Mapping: Visualize your professional and personal networks
• Automated Reports: Daily, weekly, and monthly insight summaries

🔒 Privacy & Security

• End-to-End Encryption: All data encrypted at rest and in transit
• Local Processing: Sensitive analysis performed locally when possible
• GDPR Compliant: Full data export and deletion capabilities
• Audit Logging: Complete audit trail of all data access and processing

🎯 Quick Start

Prerequisites

• Python 3.9 or higher
• Claude Desktop app or compatible MCP client
• API credentials for services you want to integrate

Installation

1. Clone the repository

git clone https://github.com/vitalune/IPA-mcp.git
cd IPA-mcp

2. Install dependencies

pip install -r requirements.txt

3. Configure API credentials

cp config/config.example.yaml config/config.yaml
# Edit config/config.yaml with your API credentials

4. Initialize the server

python -m src.main

Connect to Claude Desktop

Add this configuration to your Claude Desktop MCP settings:

{
  "mcpServers": {
    "personal-knowledge-assistant": {
      "command": "python",
      "args": ["-m", "src.main"],
      "cwd": "/path/to/IPA-mcp"
    }
  }
}

🛠️ Available Tools

The server provides 7 powerful MCP tools:

Tool	Description	Key Features
send_email	Compose and send emails with AI assistance	Smart composition, attachment support, multiple recipients
analyze_email_patterns	Analyze communication patterns and relationships	Response times, frequency analysis, sentiment tracking
post_social_media	Create and schedule social media posts	Multi-platform, optimal timing, hashtag suggestions
analyze_social_engagement	Track social media performance and insights	Engagement metrics, audience analysis, trend identification
manage_project_context	Organize projects, tasks, and deadlines	Intelligent prioritization, timeline tracking, team collaboration
track_personal_metrics	Monitor productivity, habits, and goals	Custom metrics, trend analysis, achievement tracking
generate_insights_report	Create comprehensive analytics reports	Multi-source data, actionable recommendations, export options

📖 Documentation

• Installation Guide - Detailed setup instructions
• API Setup Guide - Configure Gmail, Twitter, LinkedIn, and more
• User Guide - How to use all features effectively
• Configuration Reference - Complete configuration options
• Security Overview - Privacy and security features
• Troubleshooting - Common issues and solutions
• API Reference - Developer documentation

🔧 Configuration

Basic Configuration

# config/config.yaml
app:
  name: "Personal Knowledge Assistant"
  environment: "development"

security:
  encryption_enabled: true
  session_timeout_minutes: 60
  require_mfa: false

privacy:
  anonymize_logs: true
  data_retention_days: 90
  enable_analytics: false

integrations:
  gmail:
    enabled: true
    scopes: ["gmail.readonly", "gmail.send"]
  
  twitter:
    enabled: true
    scopes: ["tweet.read", "tweet.write"]
    
  linkedin:
    enabled: true
    scopes: ["r_liteprofile", "w_member_social"]

API Credentials

Set up your API credentials by following our detailed API Setup Guide:

• Gmail/Google Drive: Google Cloud Console OAuth 2.0
• Twitter: Twitter Developer Portal API keys
• LinkedIn: LinkedIn Developer Program credentials
• Other Services: Platform-specific setup instructions

🧪 Testing

Run the comprehensive test suite:

# Install test dependencies
pip install -r tests/requirements.txt

# Run all tests
pytest tests/

# Run specific test categories
pytest tests/unit/           # Unit tests
pytest tests/integration/    # Integration tests  
pytest tests/security/       # Security tests
pytest tests/mcp/           # MCP protocol compliance

# Generate coverage report
pytest --cov=src tests/

🚀 Example Usage

Analyze Your Email Patterns

# Ask Claude: "Analyze my email communication patterns for the last month"
# The MCP server will:
# 1. Fetch emails from the specified timeframe
# 2. Analyze response times, frequency, and relationships
# 3. Generate insights about your communication habits
# 4. Provide actionable recommendations

Cross-Platform Social Media Management

# Ask Claude: "Post about our product launch to Twitter and LinkedIn, optimized for engagement"
# The MCP server will:
# 1. Analyze your audience and engagement patterns
# 2. Suggest optimal posting times
# 3. Craft platform-appropriate content
# 4. Schedule posts across multiple platforms

Comprehensive Productivity Analysis

# Ask Claude: "Generate a weekly productivity report with insights and recommendations"
# The MCP server will:
# 1. Aggregate data from emails, calendar, and personal metrics
# 2. Identify productivity patterns and bottlenecks
# 3. Compare with previous periods
# 4. Provide personalized improvement suggestions

🏗️ Architecture

The Personal Knowledge Assistant is built with a modular, secure architecture:

├── src/
│   ├── main.py              # MCP server entry point
│   ├── tools/               # MCP tool implementations
│   ├── integrations/        # API client implementations
│   ├── utils/               # Analytics, NLP, and utilities
│   ├── models/              # Data models and schemas
│   └── config/              # Configuration and authentication
├── tests/                   # Comprehensive test suite
├── docs/                    # Documentation
└── config/                  # Configuration templates

Key Components

• MCP Protocol Layer: Standards-compliant MCP server implementation
• API Integration Layer: Secure, rate-limited connections to external services
• Analytics Engine: Advanced data processing and insight generation
• Security Layer: Encryption, authentication, and privacy controls
• Storage Layer: Secure local data storage with optional cloud sync

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes with tests
4. Run the test suite (pytest tests/)
5. Commit your changes (git commit -m 'Add amazing feature')
6. Push to the branch (git push origin feature/amazing-feature)
7. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

⚠️ Security & Privacy

Your privacy is our priority:

• Local-First: Sensitive processing happens on your machine
• Encrypted Storage: All data encrypted using industry-standard algorithms
• Minimal Data Collection: We only collect what's necessary for functionality
• Transparent Logging: Complete audit trail of all data access
• User Control: Full data export and deletion capabilities

For more details, see our Security Documentation.

🆘 Support

• Documentation: Check our comprehensive docs
• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Security: For security issues, email amirvalizadeh161@gmail.com

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